Asymmetric multivariate normal mixture GARCH

Markus Haas, Stefan Mittnik and Marc S. Paolella

Computational Statistics & Data Analysis, 2009, vol. 53, issue 6, 2129-2154

Abstract: An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the fourth moment are derived, and expressions for the dynamic correlation structure of the process are provided. In an application to stock market returns, it is shown that the disaggregation of the conditional (co)variance process generated by the model provides substantial intuition. Moreover, the model exhibits a strong performance in calculating out-of-sample Value-at-Risk measures.

Date: 2009
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Citations: View citations in EconPapers (23)

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Working Paper: Asymmetric multivariate normal mixture GARCH (2008)
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